Making wood inspection easier: FTIR spectroscopy and machine learning for Brazilian native commercial wood species identification.

Autor:	Jesus E; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br., Franca T; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br., Calvani C; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br., Lacerda M; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br., Gonçalves D; UFGD - Universidade Federal da Grande Dourados Dourados MS Brazil.; UEMS - Universidade Estadual de Mato Grosso do Sul Dourados MS Brazil., Oliveira SL; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br., Marangoni B; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br., Cena C; UFMS - Universidade Federal de Mato Grosso do Sul, Optics and Photonic Lab (SISFOTON-UFMS) Campo Grande MS Brazil cicero.cena@ufms.br.
Jazyk:	angličtina
Zdroj:	RSC advances [RSC Adv] 2024 Mar 01; Vol. 14 (11), pp. 7283-7289. Date of Electronic Publication: 2024 Mar 01 (Print Publication: 2024).
DOI:	10.1039/d4ra00174e
Abstrakt:	The molecular structure of wood is mainly based on cellulose, lignin, and hemicellulose. However, low concentrations of lipids, phenolic compounds, terpenoids, fatty acids, resin acids, and waxes can also be found. In general, their color, smell, texture, quantity, and distribution of pores are used in human sensory analysis to identify native wood species, which may lead to erroneous classification, impairing quality control and inspection of commercialized wood. This study developed a fast and accurate method to discriminate Brazilian native commercial wood species using Fourier Transform Infrared Spectroscopy (FTIR) and machine learning algorithms. It not only solves the limitations of traditional methods but also goes beyond as it allows fast analyses to be obtained at low cost and high accuracy. In this work, we provide the identification of five Brazilian native wood species: Angelim-pedra ( Hymenolobium petraeum Ducke ), Cambara ( Gochnatia polymorpha ), Cedrinho ( Erisma uncinatum ), Champagne ( Dipteryx odorata ), and Peroba do Norte ( Goupia glabra Aubl ). The results showed the great potential of FTIR and multivariate analysis for wood sample classification; here, the Linear SVM differentiated the five wood species with an accuracy of 98%. The developed method allows industries, laboratories, companies, and control bodies to identify the nature of the wood product after being extracted and semi-manufactured. Competing Interests: The authors declare the following financial interests/personal relationships, which may be considered as potential competing interests: Thiago Franca reports that Coordination of Higher Education Personnel Improvement provided financial support. (This journal is © The Royal Society of Chemistry.)
Databáze:	MEDLINE
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